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The Morphology and Circuity of Walkable and Drivable Street Networks

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  • Boeing, Geoff

    (Northeastern University)

Abstract

Circuity, the ratio of network distances to straight-line distances, is an important measure of urban street network structure and transportation efficiency. Circuity results from a circulation network's configuration, planning, and underlying terrain. In turn, it impacts how humans use urban space for settlement and travel. Although past research has examined overall street network circuity, researchers have not studied the relative circuity of walkable versus drivable circulation networks. This study uses OpenStreetMap data to explore relative network circuity. We download walkable and drivable networks for 40 US cities using the OSMnx software, which we then use to simulate four million routes and analyze circuity to characterize network structure. We find that walking networks tend to allow for more direct routes than driving networks do in most cities: average driving circuity exceeds average walking circuity in all but four of the cities that exhibit statistically significant differences between network types. We discuss various reasons for this phenomenon, illustrated with case studies. Network circuity also varies substantially between different types of places. These findings underscore the value of using network-based distances and times rather than straight-line when studying urban travel and access. They also suggest the importance of differentiating between walkable and drivable circulation networks when modeling and characterizing urban street networks: although different modes' networks overlap in any given city, their relative structure and performance vary in most cities.

Suggested Citation

  • Boeing, Geoff, 2019. "The Morphology and Circuity of Walkable and Drivable Street Networks," SocArXiv edj2s, Center for Open Science.
  • Handle: RePEc:osf:socarx:edj2s
    DOI: 10.31219/osf.io/edj2s
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    References listed on IDEAS

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    1. Geoff Boeing, 2020. "A multi-scale analysis of 27,000 urban street networks: Every US city, town, urbanized area, and Zillow neighborhood," Environment and Planning B, , vol. 47(4), pages 590-608, May.
    2. Geoff Boeing, 2020. "Planarity and street network representation in urban form analysis," Environment and Planning B, , vol. 47(5), pages 855-869, June.
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    1. Geoff Boeing, 2020. "A multi-scale analysis of 27,000 urban street networks: Every US city, town, urbanized area, and Zillow neighborhood," Environment and Planning B, , vol. 47(4), pages 590-608, May.
    2. Andrea Araldo & Andr'e de Palma & Souhila Arib & Vincent Gauthier & Romain Sere & Youssef Chaabouni & Oussama Kharouaa & Ado Adamou Abba Ari, 2020. "Pooling for First and Last Mile: Integrating Carpooling and Transit," Papers 2010.13438, arXiv.org, revised Jun 2022.
    3. Zhehao Zhang & Thomas Fisher & Gang Feng, 2020. "Assessing the Rationality and Walkability of Campus Layouts," Sustainability, MDPI, vol. 12(23), pages 1-21, December.
    4. Yong Zhang & Chao Jiang & Sheng Chen & Yuanyuan Zhang & Hui Shi & Bin Chen & Lingfeng Mao, 2021. "Effects of Landscape Attributes on Campuses Bird Species Richness and Diversity, Implications for Eco-Friendly Urban Planning," Sustainability, MDPI, vol. 13(10), pages 1-11, May.
    5. Yat Yen & Pengjun Zhao & Muhammad T Sohail, 2021. "The morphology and circuity of walkable, bikeable, and drivable street networks in Phnom Penh, Cambodia," Environment and Planning B, , vol. 48(1), pages 169-185, January.
    6. Boeing, Geoff, 2019. "Street Network Models and Measures for Every U.S. City, County, Urbanized Area, Census Tract, and Zillow-Defined Neighborhood," SocArXiv 7fxjz, Center for Open Science.
    7. Jadwiga Biegańska & Elżbieta Grzelak-Kostulska & Michał Adam Kwiatkowski, 2021. "A Typology of Attitudes towards the E-Bike against the Background of the Traditional Bicycle and the Car," Energies, MDPI, vol. 14(24), pages 1-21, December.
    8. Yang, Wenyue & Chen, Huiling & Wang, Wulin, 2020. "The path and time efficiency of residents' trips of different purposes with different travel modes: An empirical study in Guangzhou, China," Journal of Transport Geography, Elsevier, vol. 88(C).
    9. Padraig Corcoran & Rhyd Lewis, 2023. "A navigability entropy model for street networks," Environment and Planning B, , vol. 50(8), pages 2171-2186, October.
    10. Perez, Yuri & Pereira, Fabio Henrique, 2021. "Simulation of traffic light disruptions in street networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 582(C).
    11. Crispin H. V. Cooper & Ian Harvey & Scott Orford & Alain J. F. Chiaradia, 2021. "Using multiple hybrid spatial design network analysis to predict longitudinal effect of a major city centre redevelopment on pedestrian flows," Transportation, Springer, vol. 48(2), pages 643-672, April.
    12. Fernando Calderón-Figueroa, 2024. "Residential Micro-Segregation and Social Capital in Lima, Peru," Land, MDPI, vol. 13(1), pages 1-25, January.
    13. Mohammad Anwar Alattar & Caitlin Cottrill & Mark Beecroft, 2021. "Sources and Applications of Emerging Active Travel Data: A Review of the Literature," Sustainability, MDPI, vol. 13(13), pages 1-17, June.
    14. Francesca Abastante & Isabella M. Lami & Luigi La Riccia & Marika Gaballo, 2020. "Supporting Resilient Urban Planning through Walkability Assessment," Sustainability, MDPI, vol. 12(19), pages 1-20, October.

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